

'''simple docstring'''
import json
import os
import unittest

from transformers.models.blenderbot_small.tokenization_blenderbot_small import (
    VOCAB_FILES_NAMES,
    BlenderbotSmallTokenizer,
)

from ...test_tokenization_common import TokenizerTesterMixin
class 					_snake_case		(lowercase__			,			unittest.TestCase):
			__A  :	Optional[int]        =BlenderbotSmallTokenizer
			__A  :	List[Any]        =False






			def 		UpperCamelCase__							(  self     ):
				super().setUp()

				UpperCAmelCase_     :      List[str]						=  ["__start__", "adapt", "act", "ap@@", "te", "__end__", "__unk__"]
				UpperCAmelCase_     :      Any						=  dict(zip(SCREAMING_SNAKE_CASE_			,range(len(SCREAMING_SNAKE_CASE_     )     )     )     )

				UpperCAmelCase_     :      Dict						=  ["#version: 0.2", "a p", "t e</w>", "ap t</w>", "a d", "ad apt</w>", "a c", "ac t</w>", ""]
				UpperCAmelCase_     :      List[str]						=  {"unk_token": "__unk__", "bos_token": "__start__", "eos_token": "__end__"}

				UpperCAmelCase_     :      Tuple						=  os.path.join(self.tmpdirname			,VOCAB_FILES_NAMES["vocab_file"]     )
				UpperCAmelCase_     :      int						=  os.path.join(self.tmpdirname			,VOCAB_FILES_NAMES["merges_file"]     )
				with open(self.vocab_file			,"w"			,encoding="utf-8"     ) as fp:
					fp.write(json.dumps(SCREAMING_SNAKE_CASE_     ) + "\n"     )
				with open(self.merges_file			,"w"			,encoding="utf-8"     ) as fp:
					fp.write("\n".join(SCREAMING_SNAKE_CASE_     )     )






			def 		UpperCamelCase__							(  self			,**_snake_case     ):
				kwargs.update(self.special_tokens_map     )
				return BlenderbotSmallTokenizer.from_pretrained(self.tmpdirname			,**SCREAMING_SNAKE_CASE_     )






			def 		UpperCamelCase__							(  self			,_snake_case     ):
				UpperCAmelCase_     :      Tuple						=  "adapt act apte"
				UpperCAmelCase_     :      Any						=  "adapt act apte"
				return input_text, output_text






			def 		UpperCamelCase__							(  self     ):
				UpperCAmelCase_     :      int						=  BlenderbotSmallTokenizer(self.vocab_file			,self.merges_file			,**self.special_tokens_map     )
				UpperCAmelCase_     :      Dict						=  "adapt act apte"
				UpperCAmelCase_     :      Dict						=  ["adapt", "act", "ap@@", "te"]
				UpperCAmelCase_     :      int						=  tokenizer.tokenize(SCREAMING_SNAKE_CASE_     )
				self.assertListEqual(SCREAMING_SNAKE_CASE_			,SCREAMING_SNAKE_CASE_     )

				UpperCAmelCase_     :      Dict						=  [tokenizer.bos_token] + tokens + [tokenizer.eos_token]

				UpperCAmelCase_     :      int						=  [0, 1, 2, 3, 4, 5]
				self.assertListEqual(tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE_     )			,SCREAMING_SNAKE_CASE_     )






			def 		UpperCamelCase__							(  self     ):
				UpperCAmelCase_     :      Optional[Any]						=  BlenderbotSmallTokenizer.from_pretrained("facebook/blenderbot-90M"     )
				assert tok("sam"     ).input_ids == [13_84]
				UpperCAmelCase_     :      List[str]						=  "I am a small frog."
				UpperCAmelCase_     :      Tuple						=  tok([src_text]			,padding=SCREAMING_SNAKE_CASE_			,truncation=SCREAMING_SNAKE_CASE_     )["input_ids"]
				UpperCAmelCase_     :      Dict						=  tok.batch_decode(SCREAMING_SNAKE_CASE_			,skip_special_tokens=SCREAMING_SNAKE_CASE_			,clean_up_tokenization_spaces=SCREAMING_SNAKE_CASE_     )[0]
				assert src_text != decoded  # I wish it did!
				assert decoded == "i am a small frog ."






			def 		UpperCamelCase__							(  self     ):
				UpperCAmelCase_     :      List[Any]						=  BlenderbotSmallTokenizer.from_pretrained("facebook/blenderbot-90M"     )
				UpperCAmelCase_     :      List[Any]						=  "I am a small frog ."
				UpperCAmelCase_     :      Any						=  "."
				UpperCAmelCase_     :      Tuple						=  tok(SCREAMING_SNAKE_CASE_     )["input_ids"]
				UpperCAmelCase_     :      List[str]						=  tok(SCREAMING_SNAKE_CASE_     )["input_ids"]

				assert encoded[-1] == encoded_dot[0]






"""simple docstring"""






from itertools import count




def __magic_name__	(				_lowerCamelCase:		int = 50			)					->						int:

	'''simple docstring'''




	lowerCAmelCase												=  [1] * min_block_length

	for n in count(_lowerCamelCase			):
		fill_count_functions.append(1			)

		for block_length in range(_lowerCamelCase,					n + 1			):
			for block_start in range(n - block_length			):
				fill_count_functions[n] += fill_count_functions[
				    n - block_start - block_length - 1
				]

			fill_count_functions[n] += 1

		if fill_count_functions[n] > 1_000_000:
			break

	return n


if __name__ == "__main__":
					print(f"""{solution() = }""")


